Data normalization

By data normalization we understand all the data processing required to obtain georeferenced information form positioning and perception sensors. Within this topic we have focused on sensor positioning and orientation, perception sensor calibration and data co-registration.

Sensor positioning & orientation

In this topic we aim to go a step beyond on by directly applying the three geodetic pillars: correct modelling, data redundancy and data heterogeneity.

Rigorousmodelling

Rigorous modeling refers to the identification of models that approximate the physical reality beyond the sensitivity of current technology within the appropriate application context. Mathematical modeling must be both functional and stochastic. They are mutually dependent as correctness in the stochastic aspect uses to be related to simplicity in the functional formulation.

Examples of this approach are our works modelling CSAC atomic clock, a wide range of inertial sensors and all the models included in the GEMMA testbed.

Sensor redundancy

We aim improving accuracy, precision and reliability of sensor positioning and orientation through and optimal method based on redundant systems. The use of redundant systems has multiple advantages. We’d like to highlight the system noise reduction and the single fault detection and isolation.

Nowadays there are several groups working on this topic but it is still an open issue since there is not a consolidated solution for the surveying community. We are working on an approach easily transferable to the industry and the technical community.